diff --git a/app/models.py b/app/models.py
index cb7e04d3bf4a0..7cde14a588a66 100644
--- a/app/models.py
+++ b/app/models.py
@@ -1,19 +1,20 @@
 from flask.ext.appbuilder import Model
-from pydruid import client
 from datetime import timedelta
-from flask.ext.appbuilder.models.mixins import AuditMixin, FileColumn
+from flask.ext.appbuilder.models.mixins import AuditMixin
 from sqlalchemy import Column, Integer, String, ForeignKey, Text, Boolean, DateTime
 from sqlalchemy import create_engine, MetaData
 from sqlalchemy import Table as sqlaTable
 from sqlalchemy.orm import relationship
-from app import get_session
 from dateutil.parser import parse
+from pydruid import client
+from pydruid.utils.filters import Dimension, Filter
 
+from copy import deepcopy
 import logging
 import json
 import requests
 
-from app import db
+from app import db, get_session
 
 class Queryable(object):
     @property
@@ -301,6 +302,7 @@ def sync_to_db(cls, name, cluster):
             col_obj.datasource = datasource
             col_obj.generate_metrics()
         #session.commit()
+
     def query(
         self, groupby, metrics,
         granularity,
@@ -328,7 +330,38 @@ def query(
             qry['filter'] = filter
         if limit_spec:
             qry['limit_spec'] = limit_spec
+
         client = self.cluster.get_pydruid_client()
+        if timeseries_limit:
+            # Limit on the number of timeseries, doing a two-phases query
+            pre_qry = deepcopy(qry)
+            pre_qry['granularity'] = "all"
+            client.groupby(**qry)
+            df = client.export_pandas()
+            if not df is None and not df.empty:
+                dims = qry['dimensions']
+                filters = []
+                for index, row in df.iterrows():
+                    fields = []
+                    for dim in dims:
+                        f = Filter.build_filter(Dimension(dim) == row[dim])
+                        fields.append(f)
+                    if len(fields) > 1:
+                        filt = Filter(type="and", fields=fields)
+                        filters.append(Filter.build_filter(filt))
+                    elif fields:
+                        filters.append(fields[0])
+
+                if filters:
+                    ff = Filter(type="or", fields=filters)
+                    if not filter:
+                        qry['filter'] = ff
+                    else:
+                        qry['filter'] = Filter(type="and", fields=[
+                            Filter.build_filter(ff),
+                            Filter.build_filter(filter)])
+                qry['limit_spec'] = None
+
         client.groupby(**qry)
         df = client.export_pandas()
         return df
diff --git a/app/viz.py b/app/viz.py
index 2bcfcea554c9b..3ccc3fbf70b61 100644
--- a/app/viz.py
+++ b/app/viz.py
@@ -1,4 +1,3 @@
-from pydruid.utils.filters import Dimension, Filter
 from datetime import datetime
 from flask import flash, request
 import pandas as pd
@@ -7,6 +6,7 @@
 from app.highchart import Highchart
 from wtforms import Form, SelectMultipleField, SelectField, TextField
 import config
+from pydruid.utils.filters import Dimension, Filter
 
 
 CHART_ARGS = {
@@ -257,32 +257,6 @@ def bake_query(self):
         Doing a 2 phase query where we limit the number of series.
         """
         qry = self.query_obj()
-        orig_filter = qry['filter'] if 'filter' in qry else ''
-        qry['granularity'] = "all"
-        df = self.datasource.query(**qry)
-        if not df is None:
-            dims = qry['groupby']
-            filters = []
-            for index, row in df.iterrows():
-                fields = []
-                for dim in dims:
-                    f = Filter.build_filter(Dimension(dim) == row[dim])
-                    fields.append(f)
-                if len(fields) > 1:
-                    filters.append(Filter.build_filter(Filter(type="and", fields=fields)))
-                elif fields:
-                    filters.append(fields[0])
-
-            qry = self.query_obj()
-            if filters:
-                ff = Filter(type="or", fields=filters)
-                if not orig_filter:
-                    qry['filter'] = ff
-                else:
-                    qry['filter'] = Filter(type="and", fields=[
-                        Filter.build_filter(ff),
-                        Filter.build_filter(orig_filter)])
-            qry['limit_spec'] = None
         return self.datasource.query(**qry)
 
 class TimeSeriesCompareViz(TimeSeriesViz):